Resources for Drug Discovery | OpenEye Scientific

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Nicholls; Published in: Proteins: Structure, Function and Bioinformatics, 2011; Description: The results of two rounds of blind pKa predictions for ionizable residues in staphylococcal nuclease using OpenEye's legacy protein pKa prediction program based on the Zap Poisson–Boltzmann solver were submitted to the 2009 prediction challenge organized by the Protein pKa Cooperative and first round predictions were discussed at the corresponding June 2009 Telluride conference. To better understand these results, 21 additional sets of predictions were performed with the same program, varying the internal dielectric, reference pKa, partial charge set, and dielectric boundary. The internal dielectric (ϵp) and dielectric boundary were the two most important factors contributing to the quality of the predictions. Although the lowest overall errors were observed with a molecular dielectric boundary at ϵp = 8, predictions using a smooth Gaussian dielectric boundary performed almost as well at lower ϵp values because the Gaussian boundary implicitly accounts for a significant level of solvent penetration. Improved pKa predictions with the Gaussian boundary methodology will require better prediction and modeling of structural changes due to changes in ionization state, perhaps without resorting to the more exhaustive sampling of conformational states used by other recent continuum methods. 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McGann; Published in: J. Chem. Inf. Model., 2011, 51 (3), pp 578-596; Description: Results of a previous docking study are reanalyzed and extended to include results from the docking program FRED and a detailed statistical analysis of both structure reproduction and virtual screening results. FRED is run both in a traditional docking mode and in a hybrid mode that makes use of the structure of a bound ligand in addition to the protein structure to screen molecules. This analysis shows that most docking programs are effective overall but highly inconsistent, tending to do well on one system and poorly on the next. Comparing methods, the difference in mean performance on DUD is found to be statistically significant (95% confidence) 61% of the time when using a global enrichment metric (AUC). 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Model., 2010, 50(6), 1432-1440; Description: A database of about 700 high-resolution kinase structures was used to test the reliability of 17 docking procedures (using six docking software packages) by means of self- and cross-docking studies. The analysis of about 80 000 docking calculations suggests that the docking of an unknown ligand into a kinase has a probability of only 30−37% to be a correct ligand pose. However, based on the hypothesis that docking calculations are more reliable if the ligand to be docked is similar to the ligand present in the complex from which the target docking protein has been extracted, we propose an automated procedure that is able to improve the docking accuracy, suggest the best protein for docking studies, and assess the statistical reliability of docking calculations. The results were also transferred to the homology modeling field and led us to propose an alternative strategy based on ligand similarity for the development of kinase models whose experimental structure was not known. Our results suggest that in many cases this approach can give better results than the classical homology modeling procedure based exclusively on the sequence homology.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. 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Beno and D.R. Langley; Published in: J. Chem. Inf. Model., 2010, 50 (6), pp 1159-1164; Description: A frequently employed strategy in drug discovery efforts is to replace aromatic rings in known active compounds with alternative aromatic moieties to create novel compounds with improved potency and/or adsorption, distribution, metabolism, excretion, and toxicity properties. Here we introduce MORPH, which is a simple software tool for systematically modifying aromatic rings in three-dimensional models of molecules without altering the coordinates of the nonhydrogen atoms in the rings. MORPH works on individual rings as well as fused ring systems and additionally provides the ability to filter out modified compounds which do not contain hydrogen-bond donors or acceptors at specific positions on the rings or contain more or less than the desired number of heteroatoms. The MORPH program and its application to two ligands extracted from cocrystal structures with cyclin-dependent kinase 2 (CDK2)/cyclin A and CDK2 are discussed below.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. 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Fundamental measures of the interaction between molecule and aqueous phase, such as the transfer energy between gas phase and water or the energetic difference between two tautomers of a molecule in solution, remain nontrivial to predict accurately using current computational methods. SAMPL2 represents the third annual blind prediction of transfer energies, and the first time tautomer ratios were included in the challenge. Over 60 sets of predictions were submitted, and each participant also attempted to estimate the error in their predictions, a task that proved difficult for most. The results of this blind assessment of the state of the field for transfer energy and tautomer ratio prediction both indicate where the field is performing well and point out flaws in current methods.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):259-79.</span>","title":"The SAMPL2 blind prediction challenge: introduction and overview","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100430000000","publish_year":"2010","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","reference_text":"B.A. Ellingson, A.G. Skillman and A. Nicholls; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4), pp 335-342; Description: A prospective study of aqueous solvation energies was done using the SM8 and Zap TK models for a variety of geometries. CM4M charges calculated with M06 and M06-2X were found to yield similar results for the SM8 model. Zap TK calculations were primarily done with AM1BCC charges but limited attempts to use charges derived from DFT showed promise. The OMEGA application quickly generated conformations that performed well with both solvation models, while the use of computationally expensive DFT optimized geometries yielded increased RMSE and MSE. It is shown that increasing levels of gas phase geometry optimization yield increasingly unfavorable solvation energy for single conformer models.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):335-42.</span>","title":"Analysis of SM8 and Zap TK calculations and their geometric sensitivity","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"author_email":"sawp@eyesopen.com","author_name":"OpenEye Scientific","bottom_link":"","date":[{"label":"April 2010","link":"","value":"201004--"}],"has_bottom_link":false,"has_reference":false,"image":"https://cdn2.hubspot.net/hubfs/73182/2016/12/logo-banner-news-01.svg","industries":[],"interests":[],"link":"https://www.eyesopen.com/events/2010/04/eurocup-04","new_tab":false,"publish_date":"2010 4","publish_date_raw":"20100428040000","publish_year":"2010","reference_label":null,"reference_link":null,"reference_text":null,"resource_type":"Events","table_id":false,"tag":[{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1477505353977,"deletedAt":0,"description":"","id":4473799037,"label":"Event","language":null,"name":"Event","portalId":73182,"slug":"event","translatedFromId":null,"translations":{},"updated":1659735992103},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482782815969,"deletedAt":0,"description":"","id":4674213878,"label":"CUP","language":null,"name":"CUP","portalId":73182,"slug":"cup","translatedFromId":null,"translations":{},"updated":1482782815970},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482784203363,"deletedAt":0,"description":"","id":4674218968,"label":"EuroCUP","language":null,"name":"EuroCUP","portalId":73182,"slug":"eurocup","translatedFromId":null,"translations":{},"updated":1482784223778}],"tagLabel":"Event","text_snippet":"Bergisch-Gladback, Germany April 28-30, 2010 Mon, April 26th & Tues, April 27th 9:00 - 18:00 - Training on Shape-based Virtual Screening Wed, Apri...","title":"2010-04 | EuroCUP IV | Bergisch-Gladback, DE","topics":[],"types":[{"label":"Event","link":"","name":"Event","value":"Events"}],"years_within":[]},{"bottom_link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100428000000","publish_year":"2010","reference_label":null,"reference_link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","reference_text":"A.G. Skillman, M.T. Geballe and A. Nicholls; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4) pp 259-279; Description: This special issue reports on the third annual Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge and workshop. The SAMPL2 challenge was open to all and allowed participants to make blind predictions of tautomer ratios and small-molecule hydration energies. Participants were asked to make specific predictions of experimental values that were not readily available. In order to maximize participation in SAMPL2, the challenge was announced at several conferences and on CCL (ccl.net, the computational chemistry list), and practitioners who had published articles about tautomer prediction or transfer energies within the last few years were invited directly. Prior SAMPL challenges covered transfer energies, affinity predictions, virtual screening and protein-ligand co-crystal pose prediction and have been discussed elsewhere [JMC 2008, 51(4):769–779; JPC B 2009, 113(14):4501–4537]. This introduction will comment briefly on the results from SAMPL2, discuss the importance and design of prospective predictions, and introduce the next challenge, SAMPL3.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):257-8. </span>","title":"SAMPL2 challenge: prediction of solvation energies and tautomer ratios","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100406000000","publish_year":"2010","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","reference_text":"A. Nicholls, S. Wlodek and J.A. Grant; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4), pp 293-306; Description: An account is given of our contributions to the SAMPL2 challenge for vacuum-water transfer energies. These contributions include different charge sets and radii used with Poisson–Boltzmann continuum theory applied to a single low-energy conformation. A rationale for this approach is given, including a summary of what we have learnt over previous SAMPL events. The results strongly suggest the need for new and repeated experimental measurements, both to clarify what appears to be experimental discrepancies in older measurements and to advance the field in a statistically sound manner.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):293-306. </span>","title":"SAMPL2 and continuum modeling","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci900498n","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci900498n","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100401000000","publish_year":"2010","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci900498n","reference_text":"M. Lopez-Ramos and F. Perruccio","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2010, 50, 5, 801–814","title":"HPPD: Ligand- and Target-Based Virtual Screening on a Herbicide Target","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","date":[{"label":"March 2010","link":"","value":"201003--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","new_tab":1,"publish_date":"2010 3","publish_date_raw":"20100317000000","publish_year":"2010","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","reference_text":"P.C.D. Hawkins, A.G. Skillman, G.L. Warren, B.A. Ellingson and M.T. Stahl; Published in: J. Chem. Inf. Model., 2010, 50 (4), pp 572-584; Description: Here, we present the algorithm and validation for OMEGA, a systematic, knowledge-based conformer generator. The algorithm consists of three phases: assembly of an initial 3D structure from a library of fragments; exhaustive enumeration of all rotatable torsions using values drawn from a knowledge-based list of angles, thereby generating a large set of conformations; and sampling of this set by geometric and energy criteria. Validation of conformer generators like OMEGA has often been undertaken by comparing computed conformer sets to experimental molecular conformations from crystallography, usually from the Protein Databank (PDB). Such an approach is fraught with difficulty due to the systematic problems with small molecule structures in the PDB. Methods are presented to identify a diverse set of small molecule structures from cocomplexes in the PDB that has maximal reliability. A challenging set of 197 high quality, carefully selected ligand structures from well-solved models was obtained using these methods. This set will provide a sound basis for comparison and validation of conformer generators in the future. Validation results from this set are compared to the results using structures of a set of druglike molecules extracted from the Cambridge Structural Database (CSD). OMEGA is found to perform very well in reproducing the crystallographic conformations from both these data sets using two complementary metrics of success.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2010, 50, 4, 572–584","title":"Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"author_email":"sawp@eyesopen.com","author_name":"OpenEye Scientific","bottom_link":"","date":[{"label":"March 2010","link":"","value":"201003--"}],"has_bottom_link":false,"has_reference":false,"image":"https://cdn2.hubspot.net/hubfs/73182/2016/12/logo-banner-news-01.svg","industries":[],"interests":[],"link":"https://www.eyesopen.com/events/2010/03/cup-11","new_tab":false,"publish_date":"2010 3","publish_date_raw":"20100307050000","publish_year":"2010","reference_label":null,"reference_link":null,"reference_text":null,"resource_type":"Events","table_id":false,"tag":[{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1477505353977,"deletedAt":0,"description":"","id":4473799037,"label":"Event","language":null,"name":"Event","portalId":73182,"slug":"event","translatedFromId":null,"translations":{},"updated":1659735992103},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482782815969,"deletedAt":0,"description":"","id":4674213878,"label":"CUP","language":null,"name":"CUP","portalId":73182,"slug":"cup","translatedFromId":null,"translations":{},"updated":1482782815970}],"tagLabel":"Event","text_snippet":"Sunday, March 7, 2010 Afternoon session OE Toolkits - Technical Session - (organizer: Bob Tolbert, OpenEye) 2:00 Bob Tolbert, OpenEye - Better Depicti...","title":"2010-03 | CUP XI | Santa Fe, NM","topics":[],"types":[{"label":"Event","link":"","name":"Event","value":"Events"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","date":[{"label":"June 2009","link":"","value":"200906--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","new_tab":1,"publish_date":"2009 6","publish_date_raw":"20090602000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","reference_text":"M.I. Zavodsky, A. Rohatgim, J.R. Van Voorst, H. Yan and L.E. Kuhn; Published in: J. Mol. Recog., 2009, 22 (4), pp 280-292; Description: Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein–ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein–ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein–ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein–ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein–ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Mol Recognit. 2009 Jul-Aug;22(4):280-92.</span>","title":"Scoring ligand similarity in structure-based virtual screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","date":[{"label":"June 2009","link":"","value":"200906--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","new_tab":1,"publish_date":"2009 6","publish_date_raw":"20090601000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","reference_text":"G. Tresadern, D. Bemporad and T. Howe; Published in: J. Mol. Graph. and Model., 2009, 27 (8), pp 860-870; Description: Ligand based virtual screening approaches were applied to the CRF1 receptor. We compared ECFP6 fingerprints, FTrees, Topomers, Cresset FieldScreen, ROCS OpenEye shape Tanimoto, OpenEye combo-score and OpenEye electrostatics. The 3D methods OpenEye Shape Tanimoto, combo-score and Topomers performed the best at separating actives from inactives in retrospective experiments. By virtue of their higher enrichment the same methods identified more active scaffolds. However, amongst a given number of active compounds the Cresset and OpenEye electrostatic methods contained more scaffolds and returned ranked compounds with greater diversity. A selection of the methods were employed to recommend compounds for screening in a prospective experiment. New CRF1 actives antagonists were found. The new actives contained different underlying chemical architecture to the query molecules, results indicative of successful scaffold-hopping.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Mol Graph Model. 2009 Jun-Jul;27(8):860-70.</span>","title":"A Comparison of Ligand Based Virtual Screening Methods and Application to Corticotropin Releasing Factor 1 Receptor","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"author_email":"sawp@eyesopen.com","author_name":"OpenEye Scientific","bottom_link":"","date":[{"label":"April 2009","link":"","value":"200904--"}],"has_bottom_link":false,"has_reference":false,"image":"https://cdn2.hubspot.net/hubfs/73182/2016/12/logo-banner-news-01.svg","industries":[],"interests":[],"link":"https://www.eyesopen.com/events/2009/04/eurocup-03","new_tab":false,"publish_date":"2009 4","publish_date_raw":"20090422040000","publish_year":"2009","reference_label":null,"reference_link":null,"reference_text":null,"resource_type":"Events","table_id":false,"tag":[{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1477505353977,"deletedAt":0,"description":"","id":4473799037,"label":"Event","language":null,"name":"Event","portalId":73182,"slug":"event","translatedFromId":null,"translations":{},"updated":1659735992103},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482782815969,"deletedAt":0,"description":"","id":4674213878,"label":"CUP","language":null,"name":"CUP","portalId":73182,"slug":"cup","translatedFromId":null,"translations":{},"updated":1482782815970},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482784203363,"deletedAt":0,"description":"","id":4674218968,"label":"EuroCUP","language":null,"name":"EuroCUP","portalId":73182,"slug":"eurocup","translatedFromId":null,"translations":{},"updated":1482784223778}],"tagLabel":"Event","text_snippet":"Toledo, Spain April 22-23, 2009 Program for EuroCUP III, held in Toledo, Spain, April 22-24, 2009 Wednesday, April 22, 2009 Pre-meeting Toolkit Sessio...","title":"2009-04 | EuroCUP III | Toledo, ES","topics":[],"types":[{"label":"Event","link":"","name":"Event","value":"Events"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","date":[{"label":"March 2009","link":"","value":"200903--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","new_tab":1,"publish_date":"2009 3","publish_date_raw":"20090330000000","publish_year":"2009","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","reference_text":"A.J.S. Knox, T. Price, M. Pawlak, G. Golfis, C.T. Flood, D. Fayne, D.C. Williams, M.J. Meegan and D.G. Lloyd; Published in: J. Med. Chem., 2009, 52 (8), pp 2177-2180; Description: We describe the discovery of a novel indazole-based scaffold that represents the “first-in-class” dual Hsp90/tubulin binding compound. Individual known ligands for both targets shared similar 3′,4′,5′-trimethoxyphenyl cores, and from this it was hypothesized that application of an integrated ligand and structure-based virtual screening (VS) workflow could yield a single scaffold with dual binding affinity. Following validation of the VS protocol, we successfully identified a novel dual inhibitor, sourced from a commercial screening collection of 160 000 compounds.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2009, 52, 8, 2177–2180","title":"Integration of Ligand and Structure-Based Virtual Screening for the Identification of the First Dual Targeting Agent for Heat Shock Protein 90 (Hsp90) and Tubulin","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"author_email":"sawp@eyesopen.com","author_name":"OpenEye Scientific","bottom_link":"","date":[{"label":"March 2009","link":"","value":"200903--"}],"has_bottom_link":false,"has_reference":false,"image":"https://cdn2.hubspot.net/hubfs/73182/2016/12/logo-banner-news-01.svg","industries":[],"interests":[],"link":"https://www.eyesopen.com/events/2009/03/cup-10","new_tab":false,"publish_date":"2009 3","publish_date_raw":"20090308050000","publish_year":"2009","reference_label":null,"reference_link":null,"reference_text":null,"resource_type":"Events","table_id":false,"tag":[{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1477505353977,"deletedAt":0,"description":"","id":4473799037,"label":"Event","language":null,"name":"Event","portalId":73182,"slug":"event","translatedFromId":null,"translations":{},"updated":1659735992103},{"categoryId":0,"cdnPurgeEmbargoTime":null,"contentIds":[],"cosObjectType":"TAG","created":1482782815969,"deletedAt":0,"description":"","id":4674213878,"label":"CUP","language":null,"name":"CUP","portalId":73182,"slug":"cup","translatedFromId":null,"translations":{},"updated":1482782815970}],"tagLabel":"Event","text_snippet":"Location: Santa Fe, NM Dates: Mar 8-11, 2009 Program for CUP X, held in Santa Fe, New Mexico, on March 8-11, 2009 Keynote Lecture: Is protein classifi...","title":"2009-03 | CUP X | Santa Fe, NM","topics":[],"types":[{"label":"Event","link":"","name":"Event","value":"Events"}],"years_within":[]},{"bottom_link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","date":[{"label":"February 2009","link":"","value":"200902--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","new_tab":1,"publish_date":"2009 2","publish_date_raw":"20090224000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","reference_text":"R. Sayle; Published in: J. Chem. Inf. Model., 2009, 49 (3), pp 519-530; Description: Chemical compound names remain the primary method for conveying molecular structures between chemists and researchers. In research articles, patents, chemical catalogues, government legislation, and textbooks, the use of IUPAC and traditional compound names is universal, despite efforts to introduce more machine-friendly representations such as identifiers and line notations. Fortunately, advances in computing power now allow chemical names to be parsed and generated (read and written) with almost the same ease as conventional connection tables. A significant complication, however, is that although the vast majority of chemistry uses English nomenclature, a significant fraction is in other languages. This complicates the task of filing and analyzing chemical patents, purchasing from compound vendors, and text mining research articles or Web pages. We describe some issues with manipulating chemical names in various languages, including British, American, German, Japanese, Chinese, Spanish, Swedish, Polish, and Hungarian, and describe the current state-of-the-art in software tools to simplify the process.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2009, 49, 3, 519–530","title":"Foreign Language Translation of Chemical Nomenclature by Computer","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://www.nature.com/articles/nchembio.150","date":[{"label":"February 2009","link":"","value":"200902--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://www.nature.com/articles/nchembio.150","new_tab":1,"publish_date":"2009 2","publish_date_raw":"20090222000000","publish_year":"2009","reference_label":null,"reference_link":"https://www.nature.com/articles/nchembio.150","reference_text":"E. Naylor, A. Arredouani, S.R. Vasudevan, A.M. Lewis, R. Parkesh, A. Mizote, D. Rosen, J.M. Thomas, M. Izumi, A. Ganesan, A. Galione and G.C. Churchill; Published in: Nature Chemical Biology, 2009, 5, pp 220-226; Description: Research into the biological role of the Ca2+-releasing second messenger NAADP (nicotinic acid adenine dinucleotide phosphate) has been hampered by a lack of chemical probes. To find new chemical probes for exploring NAADP signaling, we turned to virtual screening, which can evaluate millions of molecules rapidly and inexpensively. We used NAADP as the query ligand to screen the chemical library ZINC for compounds with similar three-dimensional shape and electrostatic properties. We tested the top-ranking hits in a sea urchin egg bioassay and found that one hit, Ned-19, blocks NAADP signaling at nanomolar concentrations. In intact cells, Ned-19 blocked NAADP signaling and fluorescently labeled NAADP receptors. Moreover, we show the utility of Ned-19 as a chemical probe by using it to demonstrate that NAADP is a key causal link between glucose sensing and Ca2+ increases in mouse pancreatic beta cells.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<a data-test=\"journal-link\" href=\"https://www.nature.com/nchembio\" data-track=\"click\" data-track-action=\"journal homepage\" data-track-category=\"article body\" data-track-label=\"link\"><i data-test=\"journal-title\">Nature Chemical Biology</i></a><span> </span><strong data-test=\"journal-volume\"><span>volume</span> 5</strong><span>, </span><span>pages</span><span>220–226 (</span><span data-test=\"article-publication-year\">2009</span><span>)</span>","title":"Identification of a chemical probe for NAADP by virtual screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","date":[{"label":"September 2008","link":"","value":"200809--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","new_tab":1,"publish_date":"2008 9","publish_date_raw":"20080907000000","publish_year":"2008","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","reference_text":"P. Markt, R.K. Petersen, E.N Flindt, K. Kristiansen, J. Kirchmair, G. Spitzer, S. Distinito, D. Schuster, G. Wolber, C. Laggner and T. Langer; Published in: J. Med. Chem., 2008, 51 (20), pp 6303-6317; Description: Peroxisome proliferator-activated receptors (PPARs) are important targets for drugs used in the treatment of atherosclerosis, dyslipidaemia, obesity, type 2 diabetes, and other diseases caused by abnormal regulation of the glucose and lipid metabolism. We applied a virtual screening workflow based on a combination of pharmacophore modeling with 3D shape and electrostatic similarity screening techniques to discover novel scaffolds for PPAR ligands. From the resulting 10 virtual screening hits, five tested positive in human PPAR ligand-binding domain (hPPAR-LBD) transactivation assays and showed affinities for PPAR in a competitive binding assay. Compounds 5, 7, and 8 were identified as PPAR-α agonists, whereas compounds 2 and 9 showed agonistic activity for hPPAR-γ. Moreover, compound 9 was identified as a PPAR-δ antagonist. These results demonstrate that our virtual screening protocol is able to enrich novel scaffolds for PPAR ligands that could be useful for drug development in the area of atherosclerosis, dyslipidaemia, and type 2 diabetes.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2008, 51, 20, 6303–6317","title":"Discovery of Novel PPAR Ligands by a Virtual Screening Approach Based on Pharmacophore Modeling, 3D Shape, and Electrostatic Similarity Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","date":[{"label":"April 2008","link":"","value":"200804--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","new_tab":1,"publish_date":"2008 4","publish_date_raw":"20080417000000","publish_year":"2008","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","reference_text":"S.W. Muchmore, D.A. Debe, J.T. Metz, S.P. Brown, Y.C. Martin and P.J. Hajduk; Published in: J. Chem. Inf. Model., 2008, 48 (5), pp 941-948; Description: A wide variety of computational algorithms have been developed that strive to capture the chemical similarity between two compounds for use in virtual screening and lead discovery. One limitation of such approaches is that, while a returned similarity value reflects the perceived degree of relatedness between any two compounds, there is no direct correlation between this value and the expectation or confidence that any two molecules will in fact be equally active. A lack of a common framework for interpretation of similarity measures also confounds the reliable fusion of information from different algorithms. Here, we present a probabilistic framework for interpreting similarity measures that directly correlates the similarity value to a quantitative expectation that two molecules will in fact be equipotent. The approach is based on extensive benchmarking of 10 different similarity methods (MACCS keys, Daylight fingerprints, maximum common subgraphs, rapid overlay of chemical structures (ROCS) shape similarity, and six connectivity-based fingerprints) against a database of more than 150 000 compounds with activity data against 23 protein targets. Given this unified and probabilistic framework for interpreting chemical similarity, principles derived from decision theory can then be applied to combine the evidence from different similarity measures in such a way that both capitalizes on the strengths of the individual approaches and maintains a quantitative estimate of the likelihood that any two molecules will exhibit similar biological activity.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. 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Nicholls, D.L. Mobley, J.P. Guthrie, J.D. Chodera, C.I. Bayly, M.D. Cooper and V.S. Pande; Published in: J. Med. Chem., 2008, 51 (4), pp 769-779; Description: Experimental data on the transfer of small molecules between vacuum and water are relatively sparse. This makes it difficult to assess whether computational methods are truly predictive of this important quantity or merely good at explaining what has been seen. To explore this, a prospective test was performed of two different methods for estimating solvation free energies: an implicit solvent approach based on the Poisson–Boltzmann equation and an explicit solvent approach using alchemical free energy calculations. For a set of 17 small molecules, root mean square errors from experiment were between 1.3 and 2.6 kcal/mol, with the explicit solvent free energy approach yielding somewhat greater accuracy but at greater computational expense. 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McGaughey, R.P. Sheridan, C.I. Bayly, J.C. Culberson, C. Kreatsolas, S. Lindsley, V. Maiorov, J.-F. Truchon and W.D. Cornell; Published in: J. Chem. Inf. Model., 2007, 47 (4), pp 1504-1519","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. 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Model., 2007, 47 (4), pp 1504-1519; Description: Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. 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Grant, B.T. Pickup, M.J. Sykes, C.A. Kitchen and A. Nicholls; Published in: Chemical Physics Letters, 2007, 441 (1-3), pp 163-166; Description: This work introduces the ‘Sheffield Solvation’ model for calculating the electrostatic component of molecular solvation energy. The resulting formula can be included in standard modelling technology with very low computational cost. The model replaces detailed information about local atomic environments (such as found in Generalised Born approaches), by using two global parameters. 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Our implementation is based on a pattern-matching finite state machine (FSM) which results in fast search times. The accuracy of LINGO is demonstrated to be comparable to that of a path-based fingerprint and offers a simple yet effective method for similarity searching.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. 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Brown and S.W. Muchmore; Published in: J. Chem. Inf. Model., 2006, 46 (3), pp 999-1005; Description: We have developed a system for performing computations on an enterprise grid using a freely available package for grid computing that allows us to harvest unused CPU cycles off of employee desktop computers. By modifying the traditional formulation of Molecular Mechanics with Poisson−Boltzmann Surface Area (MM-PBSA) methodology, in combination with a coarse-grain parallelized implementation suitable for deployment onto our enterprise grid, we show that it is possible to produce rapid physics-based estimates of protein−ligand binding affinities that have good correlation to experimental data. 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Akritopoulou-Zanze; Published in: Chemical Biology & Drug Design, 2006, 67 (2), pp 174-176; Description: To aid in the identification of novel melanin-concentrating hormone receptor 1 (MCHr1) antagonists, a unique virtual library of readily synthesized molecules was designed and assembled based on 323 monomer compounds containing reactive moieties in combination with 30 core molecules having diamine functionality. The resulting library of 3 129 870 molecules was searched using three-dimensional shape similarity measures that were complimented with a novel electrostatic distribution similarity-matching algorithm. One of the top scoring hits in this library was synthesized and characterized for MCHr1 antagonism, where it exhibited at least a threefold improvement in binding affinity and cellular potency relative to the parent MCHr1 ligand. This work demonstrates that the use of shape and electrostatic similarity matching in combination with a well-designed virtual library can be used to augment standard medicinal chemistry techniques.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>Chem Biol Drug Des. 2006 Feb;67(2):174-6.</span>","title":"The Use of Three-Dimensional Shape and Electrostatic Similarity Searching in the Identification of a Melanin-Concentrating Hormone Receptor 1 Antagonist","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/15743191/","date":[{"label":"March 2005","link":"","value":"200503--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/15743191/","new_tab":1,"publish_date":"2005 3","publish_date_raw":"20050310000000","publish_year":"2005","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/15743191/","reference_text":"Rush TS 3rd, Grant JA, Mosyak L, Nicholls A. 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Irwin and B.K. Shoichet; Published in: J. Chem. Inf. Model., 2005, 45 (1), pp 177-182; Description: A critical barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compounds. We have therefore prepared a library of 727 842 molecules, each with 3D structure, using catalogs of compounds from vendors (the size of this library continues to grow). The molecules have been assigned biologically relevant protonation states and are annotated with properties such as molecular weight, calculated LogP, and number of rotatable bonds. Each molecule in the library contains vendor and purchasing information and is ready for docking using a number of popular docking programs. Within certain limits, the molecules are prepared in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the molecules. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a molecular drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own molecules by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2005, 45, 1, 177–182","title":"ZINC - A Free Database of Commercially Available Compounds for Virtual Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","date":[{"label":"October 2004","link":"","value":"200410--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","new_tab":1,"publish_date":"2004 10","publish_date_raw":"20041012000000","publish_year":"2004","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","reference_text":"N.V. Prabhu, P. Zhu and K.A. Sharp; Published in: J. Comp. Chem., 2004, 25 (16), pp 2049-2064; Description: A fast stable finite difference Poisson–Boltzmann (FDPB) model for implicit solvation in molecular dynamics simulations was developed using the smooth permittivity FDPB method implemented in the OpenEye ZAP libraries. This was interfaced with two widely used molecular dynamics packages, AMBER and CHARMM. Using the CHARMM-ZAP software combination, the implicit solvent model was tested on eight proteins differing in size, structure, and cofactors: calmodulin, horseradish peroxidase (with and without substrate analogue bound), lipid carrier protein, flavodoxin, ubiquitin, cytochrome c, and a de novo designed 3-helix bundle. The stability and accuracy of the implicit solvent simulations was assessed by examining root-mean-squared deviations from crystal structure. This measure was compared with that of a standard explicit water solvent model. In addition we compared experimental and calculated NMR order parameters to obtain a residue level assessment of the accuracy of MD-ZAP for simulating dynamic quantities. Overall, the agreement of the implicit solvent model with experiment was as good as that of explicit water simulations. The implicit solvent method was up to eight times faster than the explicit water simulations, and approximately four times slower than a vacuum simulation (i.e., with no solvent treatment).","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Chem. 2004 Dec;25(16):2049-64.</span>","title":"Implementation and testing of stable, fast implicit solvation in molecular dynamics using the smooth-permittivity finite difference Poisson-Boltzmann method","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","date":[{"label":"April 2004","link":"","value":"200404--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","new_tab":1,"publish_date":"2004 4","publish_date_raw":"20040407000000","publish_year":"2004","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","reference_text":"E. Perola and P.S. Charifson; Published in: J. Med. Chem., 2004, 47 (10), pp 2499-2510; Description: This paper describes a large-scale study on the nature and the energetics of the conformational changes drug-like molecules experience upon binding. Ligand strain energies and conformational reorganization were analyzed with different computational methods on 150 crystal structures of pharmaceutically relevant protein−ligand complexes. The common knowledge that ligands rarely bind in their lowest calculated energy conformation was confirmed. Additionally, we found that over 60% of the ligands do not bind in a local minimum conformation. While approximately 60% of the ligands were calculated to bind with strain energies lower than 5 kcal/mol, strain energies over 9 kcal/mol were calculated in at least 10% of the cases regardless of the method used. A clear correlation was found between acceptable strain energy and ligand flexibility, while there was no correlation between strain energy and binding affinity, thus indicating that expensive conformational rearrangements can be tolerated in some cases without overly penalizing the tightness of binding. On the basis of the trends observed, thresholds for the acceptable strain energies of bioactive conformations were defined with consideration of the impact of ligand flexibility. An analysis of the degree of folding of the bound ligands confirmed the general tendency of small molecules to bind in an extended conformation. The results suggest that the unfolding of hydrophobic ligands during binding, which exposes hydrophobic surfaces to contact with protein residues, could be one of the factors accounting for high reorganization energies. Finally, different methods for conformational analysis were evaluated, and guidelines were defined to maximize the prevalence of bioactive conformations in computationally generated ensembles.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2004, 47, 10, 2499–2510","title":"Conformational Analysis of Drug-Like Molecules Bound to Proteins: An Extensive Study of Ligand Reorganization upon Binding","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","date":[{"label":"January 2004","link":"","value":"200401--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","new_tab":1,"publish_date":"2004 1","publish_date_raw":"20040123000000","publish_year":"2004","reference_label":null,"reference_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","reference_text":"G.E. Kellogg, S. Phatak, A. Nicholls and J.A. Grant; Published in: QSAR & Combinatorial Science, 2004, 22 (9-10), pp 959-964; Description: A CoMFA 3D QSAR (Quantitative Structure-Activity Relationships) study was performed on five diverse data sets that have been previously published or are otherwise generally available to assess the value of the ZAP electrostatic potential field (calculated from a solution of the Poisson-Boltzmann Equation) as compared to the Coulombic field as implemented in standard CoMFA. The ZAP field showed an average improvement of 0.114 in q2 (leave-one-out cross-validation) as compared to the Coulombic field, and the steric/ZAP combination field showed an improvement of 0.128 in q2 as compared to the Both (steric and electrostatic) field combination of CoMFA. However, the enhancement is not monolithic – some of the data sets in this study showed a much larger preference for the ZAP field than others. The ZAP field appears to be more physically realistic than the Coulombic field and should be of significant value in QSAR studies of some data sets.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<p>QSAR & Combinatorial Science Volume22, Issue9-10, January 2004.</p>","title":"Validation of Poisson-Boltzmann Electrostatic Potential Fields in 3D QSAR: A CoMFA Study on Multiple Datasets","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","date":[{"label":"December 2002","link":"","value":"200212--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","new_tab":1,"publish_date":"2002 12","publish_date_raw":"20021202000000","publish_year":"2002","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","reference_text":"M.R. McGann, H.R. Almond, A. Nicholls, J.A. Grant and F.K. Brown; Published in: Biopolymers, 2003,68 (1), pp 76-90; Description: A shape-based Gaussian docking function is constructed which uses Gaussian functions to represent the shapes of individual atoms. A set of 20 trypsin ligand–protein complexes are drawn from the Protein Data Bank (PDB), the ligands are separated from the proteins, and then are docked back into the active sites using numerical optimization of this function. It is found that by employing this docking function, quasi-Newton optimization is capable of moving ligands great distances [on average 7 Å root mean square distance (RMSD)] to locate the correctly docked structure. It is also found that a ligand drawn from one PDB file can be docked into a trypsin structure drawn from any of the trypsin PDB files. This implies that this scoring function is not limited to more accurate x-ray structures, as is the case for many of the conventional docking methods, but could be extended to homology models. © 2002 Wiley Periodicals, Inc. Biopolymers 68: 76–90, 2003","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>Biopolymers. 2003 Jan;68(1):76-90.</span>","title":"Gaussian docking functions","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","date":[{"label":"March 2001","link":"","value":"200103--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","new_tab":1,"publish_date":"2001 3","publish_date_raw":"20010320000000","publish_year":"2001","reference_label":null,"reference_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","reference_text":"J.A. Grant, B.T. Pickup and A. Nicholls; Published in: J. Comp. Chem., 2001, 22 (6), pp 608-640; Description: This work introduces a continuous smooth permittivity function into Poisson–Boltzmann techniques for continuum approaches to modeling the solvation of small molecules and proteins. The permittivity function is derived using a Gaussian method to describe volume exclusion. The new method allows a rigorous determination of solvent forces within a grid-based technology. The generality of approach is demonstrated by considering a range of applications for small molecules and macromolecules. We also present a very complete statistical analysis of grid errors, and show that the accuracy of our Gaussian-based method is improved over standard techniques. The method has been implemented in a new code called ZAP, which is freely available to academic institutions.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<p>Journal of Computational Chemistry: Volume 22, Issue 6, Pages: 565-672, 30 April 2001.</p>","title":"A Smooth Permittivity Function for Poisson-Boltzmann Solvation Methods","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]}]; // console.log(fullData); var grouped_types = [{"label":"On-Demand Webinars","name":"On-Demand 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Churchill; Published in: Nature Chemical Biology, 2009, 5, pp 220-226; Description: Research into the biological role of the Ca2+-releasing second messenger NAADP (nicotinic acid adenine dinucleotide phosphate) has been hampered by a lack of chemical probes. To find new chemical probes for exploring NAADP signaling, we turned to virtual screening, which can evaluate millions of molecules rapidly and inexpensively. We used NAADP as the query ligand to screen the chemical library ZINC for compounds with similar three-dimensional shape and electrostatic properties. We tested the top-ranking hits in a sea urchin egg bioassay and found that one hit, Ned-19, blocks NAADP signaling at nanomolar concentrations. In intact cells, Ned-19 blocked NAADP signaling and fluorescently labeled NAADP receptors. Moreover, we show the utility of Ned-19 as a chemical probe by using it to demonstrate that NAADP is a key causal link between glucose sensing and Ca2+ increases in mouse pancreatic beta cells.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<a data-test=\"journal-link\" href=\"https://www.nature.com/nchembio\" data-track=\"click\" data-track-action=\"journal homepage\" data-track-category=\"article body\" data-track-label=\"link\"><i data-test=\"journal-title\">Nature Chemical Biology</i></a><span>&nbsp;</span><strong data-test=\"journal-volume\"><span>volume</span>&nbsp;5</strong><span>,&nbsp;</span><span>pages</span><span>220–226 (</span><span data-test=\"article-publication-year\">2009</span><span>)</span>","title":"Identification of a chemical probe for NAADP by virtual screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","date":[{"label":"June 2009","link":"","value":"200906--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","new_tab":1,"publish_date":"2009 6","publish_date_raw":"20090602000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/19235177/","reference_text":"M.I. Zavodsky, A. Rohatgim, J.R. Van Voorst, H. Yan and L.E. Kuhn; Published in: J. Mol. Recog., 2009, 22 (4), pp 280-292; Description: Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein–ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein–ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein–ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein–ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein–ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Mol Recognit. 2009 Jul-Aug;22(4):280-92.</span>","title":"Scoring ligand similarity in structure-based virtual screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","date":[{"label":"June 2009","link":"","value":"200906--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","new_tab":1,"publish_date":"2009 6","publish_date_raw":"20090601000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/19230731/","reference_text":"G. Tresadern, D. Bemporad and T. Howe; Published in: J. Mol. Graph. and Model., 2009, 27 (8), pp 860-870; Description: Ligand based virtual screening approaches were applied to the CRF1 receptor. We compared ECFP6 fingerprints, FTrees, Topomers, Cresset FieldScreen, ROCS OpenEye shape Tanimoto, OpenEye combo-score and OpenEye electrostatics. The 3D methods OpenEye Shape Tanimoto, combo-score and Topomers performed the best at separating actives from inactives in retrospective experiments. By virtue of their higher enrichment the same methods identified more active scaffolds. However, amongst a given number of active compounds the Cresset and OpenEye electrostatic methods contained more scaffolds and returned ranked compounds with greater diversity. A selection of the methods were employed to recommend compounds for screening in a prospective experiment. New CRF1 actives antagonists were found. The new actives contained different underlying chemical architecture to the query molecules, results indicative of successful scaffold-hopping.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Mol Graph Model. 2009 Jun-Jul;27(8):860-70.</span>","title":"A Comparison of Ligand Based Virtual Screening Methods and Application to Corticotropin Releasing Factor 1 Receptor","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","date":[{"label":"September 2008","link":"","value":"200809--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","new_tab":1,"publish_date":"2008 9","publish_date_raw":"20080907000000","publish_year":"2008","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm800128k","reference_text":"P. Markt, R.K. Petersen, E.N Flindt, K. Kristiansen, J. Kirchmair, G. Spitzer, S. Distinito, D. Schuster, G. Wolber, C. Laggner and T. Langer; Published in: J. Med. Chem., 2008, 51 (20), pp 6303-6317; Description: Peroxisome proliferator-activated receptors (PPARs) are important targets for drugs used in the treatment of atherosclerosis, dyslipidaemia, obesity, type 2 diabetes, and other diseases caused by abnormal regulation of the glucose and lipid metabolism. We applied a virtual screening workflow based on a combination of pharmacophore modeling with 3D shape and electrostatic similarity screening techniques to discover novel scaffolds for PPAR ligands. From the resulting 10 virtual screening hits, five tested positive in human PPAR ligand-binding domain (hPPAR-LBD) transactivation assays and showed affinities for PPAR in a competitive binding assay. Compounds 5, 7, and 8 were identified as PPAR-α agonists, whereas compounds 2 and 9 showed agonistic activity for hPPAR-γ. Moreover, compound 9 was identified as a PPAR-δ antagonist. These results demonstrate that our virtual screening protocol is able to enrich novel scaffolds for PPAR ligands that could be useful for drug development in the area of atherosclerosis, dyslipidaemia, and type 2 diabetes.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2008, 51, 20, 6303–6317","title":"Discovery of Novel PPAR Ligands by a Virtual Screening Approach Based on Pharmacophore Modeling, 3D Shape, and Electrostatic Similarity Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/16492165/","date":[{"label":"January 2006","link":"","value":"200601--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/16492165/","new_tab":1,"publish_date":"2006 1","publish_date_raw":"20060131000000","publish_year":"2006","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/16492165/","reference_text":"S.W. Muchmore, A.J. Souers and I. Akritopoulou-Zanze; Published in: Chemical Biology & Drug Design, 2006, 67 (2), pp 174-176; Description: To aid in the identification of novel melanin-concentrating hormone receptor 1 (MCHr1) antagonists, a unique virtual library of readily synthesized molecules was designed and assembled based on 323 monomer compounds containing reactive moieties in combination with 30 core molecules having diamine functionality. The resulting library of 3 129 870 molecules was searched using three-dimensional shape similarity measures that were complimented with a novel electrostatic distribution similarity-matching algorithm. One of the top scoring hits in this library was synthesized and characterized for MCHr1 antagonism, where it exhibited at least a threefold improvement in binding affinity and cellular potency relative to the parent MCHr1 ligand. This work demonstrates that the use of shape and electrostatic similarity matching in combination with a well-designed virtual library can be used to augment standard medicinal chemistry techniques.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>Chem Biol Drug Des. 2006 Feb;67(2):174-6.</span>","title":"The Use of Three-Dimensional Shape and Electrostatic Similarity Searching in the Identification of a Melanin-Concentrating Hormone Receptor 1 Antagonist","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/22669221/","date":[{"label":"June 2012","link":"","value":"201206--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/22669221/","new_tab":1,"publish_date":"2012 6","publish_date_raw":"20120605000000","publish_year":"2012","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/22669221/","reference_text":"M. McGann; Published in: J. Comp.-Aid. Mol. Design, 2012, 26, pp 897-906; Description: The docking performance of the FRED and HYBRID programs are evaluated on two standardized datasets from the Docking and Scoring Symposium of the ACS Spring 2011 national meeting. The evaluation includes cognate docking and virtual screening performance. FRED docks 70 % of the structures to within 2 Å in the cognate docking test. In the virtual screening test, FRED is found to have a mean AUC of 0.75. The HYBRID program uses a modified version of FRED’s algorithm that uses both ligand- and structure-based information to dock molecules, which increases its mean AUC to 0.78. HYBRID can also implicitly account for protein flexibility by making use of multiple crystal structures. Using multiple crystal structures improves HYBRID’s performance (mean AUC 0.80) with a negligible increase in docking time (~15 %).","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2012 Aug;26(8):897-906.&nbsp;</span>","title":"FRED and HYBRID Docking Performance on Standardized Datasets","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci100436p","date":[{"label":"February 2011","link":"","value":"201102--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci100436p","new_tab":1,"publish_date":"2011 2","publish_date_raw":"20110216000000","publish_year":"2011","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci100436p","reference_text":"M. McGann; Published in: J. Chem. Inf. Model., 2011, 51 (3), pp 578-596; Description: Results of a previous docking study are reanalyzed and extended to include results from the docking program FRED and a detailed statistical analysis of both structure reproduction and virtual screening results. FRED is run both in a traditional docking mode and in a hybrid mode that makes use of the structure of a bound ligand in addition to the protein structure to screen molecules. This analysis shows that most docking programs are effective overall but highly inconsistent, tending to do well on one system and poorly on the next. Comparing methods, the difference in mean performance on DUD is found to be statistically significant (95% confidence) 61% of the time when using a global enrichment metric (AUC). Early enrichment metrics are found to have relatively poor statistical power, with 0.5% early enrichment only able to distinguish methods to 95% confidence 14% of the time.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2011, 51, 3, 578–596","title":"FRED Pose Prediction and Virtual Screening Accuracy","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci100161z","date":[{"label":"July 2010","link":"","value":"201007--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci100161z","new_tab":1,"publish_date":"2010 7","publish_date_raw":"20100727000000","publish_year":"2010","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci100161z","reference_text":"Tuccinardi, M. Botta, A. Giordano, and A. Martinelli; Published in: J. Chem. Inf. Model., 2010, 50(6), 1432-1440; Description: A database of about 700 high-resolution kinase structures was used to test the reliability of 17 docking procedures (using six docking software packages) by means of self- and cross-docking studies. The analysis of about 80 000 docking calculations suggests that the docking of an unknown ligand into a kinase has a probability of only 30−37% to be a correct ligand pose. However, based on the hypothesis that docking calculations are more reliable if the ligand to be docked is similar to the ligand present in the complex from which the target docking protein has been extracted, we propose an automated procedure that is able to improve the docking accuracy, suggest the best protein for docking studies, and assess the statistical reliability of docking calculations. The results were also transferred to the homology modeling field and led us to propose an alternative strategy based on ligand similarity for the development of kinase models whose experimental structure was not known. Our results suggest that in many cases this approach can give better results than the classical homology modeling procedure based exclusively on the sequence homology.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2010, 50, 8, 1432–1441","title":"Protein Kinases: Docking and Homology Modeling Reliability","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","date":[{"label":"March 2009","link":"","value":"200903--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","new_tab":1,"publish_date":"2009 3","publish_date_raw":"20090330000000","publish_year":"2009","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm801569z","reference_text":"A.J.S. Knox, T. Price, M. Pawlak, G. Golfis, C.T. Flood, D. Fayne, D.C. Williams, M.J. Meegan and D.G. Lloyd; Published in: J. Med. Chem., 2009, 52 (8), pp 2177-2180; Description: We describe the discovery of a novel indazole-based scaffold that represents the “first-in-class” dual Hsp90/tubulin binding compound. Individual known ligands for both targets shared similar 3′,4′,5′-trimethoxyphenyl cores, and from this it was hypothesized that application of an integrated ligand and structure-based virtual screening (VS) workflow could yield a single scaffold with dual binding affinity. Following validation of the VS protocol, we successfully identified a novel dual inhibitor, sourced from a commercial screening collection of 160 000 compounds.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2009, 52, 8, 2177–2180","title":"Integration of Ligand and Structure-Based Virtual Screening for the Identification of the First Dual Targeting Agent for Heat Shock Protein 90 (Hsp90) and Tubulin","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","date":[{"label":"June 2007","link":"","value":"200706--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","new_tab":1,"publish_date":"2007 6","publish_date_raw":"20070626000000","publish_year":"2007","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","reference_text":"G.B. McGaughey, R.P. Sheridan, C.I. Bayly, J.C. Culberson, C. Kreatsolas, S. Lindsley, V. Maiorov, J.-F. Truchon and W.D. Cornell; Published in: J. Chem. Inf. Model., 2007, 47 (4), pp 1504-1519","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2007, 47, 4, 1504–1519","title":"Comparison of Topological, Shape, and Docking Methods in Virtual Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","date":[{"label":"December 2002","link":"","value":"200212--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","new_tab":1,"publish_date":"2002 12","publish_date_raw":"20021202000000","publish_year":"2002","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/12579581/","reference_text":"M.R. McGann, H.R. Almond, A. Nicholls, J.A. Grant and F.K. Brown; Published in: Biopolymers, 2003,68 (1), pp 76-90; Description: A shape-based Gaussian docking function is constructed which uses Gaussian functions to represent the shapes of individual atoms. A set of 20 trypsin ligand–protein complexes are drawn from the Protein Data Bank (PDB), the ligands are separated from the proteins, and then are docked back into the active sites using numerical optimization of this function. It is found that by employing this docking function, quasi-Newton optimization is capable of moving ligands great distances [on average 7 Å root mean square distance (RMSD)] to locate the correctly docked structure. It is also found that a ligand drawn from one PDB file can be docked into a trypsin structure drawn from any of the trypsin PDB files. This implies that this scoring function is not limited to more accurate x-ray structures, as is the case for many of the conventional docking methods, but could be extended to homology models. © 2002 Wiley Periodicals, Inc. Biopolymers 68: 76–90, 2003","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>Biopolymers. 2003 Jan;68(1):76-90.</span>","title":"Gaussian docking functions","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci3000419","date":[{"label":"April 2012","link":"","value":"201204--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci3000419","new_tab":1,"publish_date":"2012 4","publish_date_raw":"20120407000000","publish_year":"2012","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci3000419","reference_text":"E.O. Cannon; Published in: J. Chem. Inf. Model., 2012; Description: We propose a new, robust benchmark, called Percentage Round Tripping of Canonical Isomeric SMILES (%RTCS), for assessing the ability of chemical nomenclature software to convert chemical structures to names and chemical names to structures. The benchmark is based on a string comparison between canonical isomeric SMILES generated from the original structure and the resultant structure from round tripping. Using the latest version of the OpenEye chemical nomenclature toolkit, Lexichem v2.1.0, we report %RTCS values of over 92% on average for a variety of challenging compound collections.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2012, 52, 5, 1124–1131","title":"New Benchmark for Chemical Nomenclature Software","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci9004964","date":[{"label":"May 2010","link":"","value":"201005--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci9004964","new_tab":1,"publish_date":"2010 5","publish_date_raw":"20100518000000","publish_year":"2010","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci9004964","reference_text":"B.R. Beno and D.R. Langley; Published in: J. Chem. Inf. Model., 2010, 50 (6), pp 1159-1164; Description: A frequently employed strategy in drug discovery efforts is to replace aromatic rings in known active compounds with alternative aromatic moieties to create novel compounds with improved potency and/or adsorption, distribution, metabolism, excretion, and toxicity properties. Here we introduce MORPH, which is a simple software tool for systematically modifying aromatic rings in three-dimensional models of molecules without altering the coordinates of the nonhydrogen atoms in the rings. MORPH works on individual rings as well as fused ring systems and additionally provides the ability to filter out modified compounds which do not contain hydrogen-bond donors or acceptors at specific positions on the rings or contain more or less than the desired number of heteroatoms. The MORPH program and its application to two ligands extracted from cocrystal structures with cyclin-dependent kinase 2 (CDK2)/cyclin A and CDK2 are discussed below.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2010, 50, 6, 1159–1164","title":"MORPH: A New Tool for Ligand Design","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","date":[{"label":"February 2009","link":"","value":"200902--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","new_tab":1,"publish_date":"2009 2","publish_date_raw":"20090224000000","publish_year":"2009","reference_label":null,"reference_link":"https://pubs.acs.org/doi/full/10.1021/ci800243w","reference_text":"R. Sayle; Published in: J. Chem. Inf. Model., 2009, 49 (3), pp 519-530; Description: Chemical compound names remain the primary method for conveying molecular structures between chemists and researchers. In research articles, patents, chemical catalogues, government legislation, and textbooks, the use of IUPAC and traditional compound names is universal, despite efforts to introduce more machine-friendly representations such as identifiers and line notations. Fortunately, advances in computing power now allow chemical names to be parsed and generated (read and written) with almost the same ease as conventional connection tables. A significant complication, however, is that although the vast majority of chemistry uses English nomenclature, a significant fraction is in other languages. This complicates the task of filing and analyzing chemical patents, purchasing from compound vendors, and text mining research articles or Web pages. We describe some issues with manipulating chemical names in various languages, including British, American, German, Japanese, Chinese, Spanish, Swedish, Polish, and Hungarian, and describe the current state-of-the-art in software tools to simplify the process.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2009, 49, 3, 519–530","title":"Foreign Language Translation of Chemical Nomenclature by Computer","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci6002152","date":[{"label":"September 2006","link":"","value":"200609--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci6002152","new_tab":1,"publish_date":"2006 9","publish_date_raw":"20060908000000","publish_year":"2006","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci6002152","reference_text":"J.A. Grant, J.A. Haigh, B.T. Pickup, A. Nicholls and R.A. Sayle; Published in: J. Chem. Inf. Model., 2006, 46 (5), pp 1912-1918; Description: We apply a recently published method of text-based molecular similarity searching (LINGO) to standard data sets for the purpose of quantifying the accuracy of the approach. Our implementation is based on a pattern-matching finite state machine (FSM) which results in fast search times. The accuracy of LINGO is demonstrated to be comparable to that of a path-based fingerprint and offers a simple yet effective method for similarity searching.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2006, 46, 5, 1912–1918","title":"Lingos, Finite State Machines, and Fast Similarity Searching","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci049714%2B","date":[{"label":"December 2004","link":"","value":"200412--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci049714%2B","new_tab":1,"publish_date":"2004 12","publish_date_raw":"20041214000000","publish_year":"2004","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci049714%2B","reference_text":"J.J. Irwin and B.K. Shoichet; Published in: J. Chem. Inf. Model., 2005, 45 (1), pp 177-182; Description: A critical barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compounds. We have therefore prepared a library of 727 842 molecules, each with 3D structure, using catalogs of compounds from vendors (the size of this library continues to grow). The molecules have been assigned biologically relevant protonation states and are annotated with properties such as molecular weight, calculated LogP, and number of rotatable bonds. Each molecule in the library contains vendor and purchasing information and is ready for docking using a number of popular docking programs. Within certain limits, the molecules are prepared in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the molecules. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a molecular drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own molecules by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2005, 45, 1, 177–182","title":"ZINC - A Free Database of Commercially Available Compounds for Virtual Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubs.acs.org/doi/10.1021/acs.jcim.0c00358","date":[{"label":"June 2020","link":"","value":"202006--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubs.acs.org/doi/10.1021/acs.jcim.0c00358","new_tab":1,"publish_date":"2020 6","publish_date_raw":"20200623000000","publish_year":"2020","reference_label":null,"reference_link":"https://pubs.acs.org/doi/10.1021/acs.jcim.0c00358","reference_text":"Paul C.D. Hawkins and Stanislaw Wlodek","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2020, 60 (7), pp. 3518-3533.","title":"Decisions with Confidence: Application to the Conformation Sampling of Molecules in the Solid State","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[{"label":"Within 10 years","link":"","value":"year-10"},{"label":"Within 5 years","link":"","value":"year-5"}]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci300314k","date":[{"label":"October 2012","link":"","value":"201210--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci300314k","new_tab":1,"publish_date":"2012 10","publish_date_raw":"20121019000000","publish_year":"2012","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci300314k","reference_text":"P.C.D. Hawkins and A. Nicholls; Published in: J. Chem. Inf. Model. 2012, 52, pp. 2919-2936; Description: We recently published a high quality validation set for testing conformer generators, consisting of structures from both the PDB and the CSD (Hawkins, P. C. D. et al. J. Chem. Inf. Model.2010, 50, 572.), and tested the performance of our conformer generator, OMEGA, on these sets. In the present publication, we focus on understanding the suitability of those data sets for validation and identifying and learning from OMEGA’s failures. We compare, for the first time we are aware of, the coverage of the applicable property spaces between the validation data sets we used and the parent compound sets to determine if our data sets adequately sample these property spaces. We also introduce the concept of torsion fingerprinting and compare this method of dissimilation to the more traditional graph-centric diversification methods we used in our previous publication. To improve our ability to programmatically identify cases where the crystallographic conformation is not well reproduced computationally, we introduce a new metric to compare conformations, RMSTanimoto. This new metric is used alongside those from our previous publication to efficiently identify reproduction failures. We find RMSTanimoto to be particularly effective in identifying failures for the smallest molecules in our data sets. Analysis of the nature of these failures, particularly those for the CSD, sheds further light on the issue of strain in crystallographic structures. Some of the residual failure cases not resolved by simple changes in OMEGA’s defaults present significant challenges to conformer generation engines like OMEGA and are a source of new avenues to further improve their performance, while others illustrate the pitfalls of validating against crystallographic ligand conformations, particularly those from the PDB.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2012, 52, 11, 2919–2936","title":"Conformer Generation with OMEGA: Learning from the Data Set and the Analysis of Failures","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","date":[{"label":"March 2010","link":"","value":"201003--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","new_tab":1,"publish_date":"2010 3","publish_date_raw":"20100317000000","publish_year":"2010","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci100031x","reference_text":"P.C.D. Hawkins, A.G. Skillman, G.L. Warren, B.A. Ellingson and M.T. Stahl; Published in: J. Chem. Inf. Model., 2010, 50 (4), pp 572-584; Description: Here, we present the algorithm and validation for OMEGA, a systematic, knowledge-based conformer generator. The algorithm consists of three phases: assembly of an initial 3D structure from a library of fragments; exhaustive enumeration of all rotatable torsions using values drawn from a knowledge-based list of angles, thereby generating a large set of conformations; and sampling of this set by geometric and energy criteria. Validation of conformer generators like OMEGA has often been undertaken by comparing computed conformer sets to experimental molecular conformations from crystallography, usually from the Protein Databank (PDB). Such an approach is fraught with difficulty due to the systematic problems with small molecule structures in the PDB. Methods are presented to identify a diverse set of small molecule structures from cocomplexes in the PDB that has maximal reliability. A challenging set of 197 high quality, carefully selected ligand structures from well-solved models was obtained using these methods. This set will provide a sound basis for comparison and validation of conformer generators in the future. Validation results from this set are compared to the results using structures of a set of druglike molecules extracted from the Cambridge Structural Database (CSD). OMEGA is found to perform very well in reproducing the crystallographic conformations from both these data sets using two complementary metrics of success.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2010, 50, 4, 572–584","title":"Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","date":[{"label":"April 2004","link":"","value":"200404--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","new_tab":1,"publish_date":"2004 4","publish_date_raw":"20040407000000","publish_year":"2004","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm030563w","reference_text":"E. Perola and P.S. Charifson; Published in: J. Med. Chem., 2004, 47 (10), pp 2499-2510; Description: This paper describes a large-scale study on the nature and the energetics of the conformational changes drug-like molecules experience upon binding. Ligand strain energies and conformational reorganization were analyzed with different computational methods on 150 crystal structures of pharmaceutically relevant protein−ligand complexes. The common knowledge that ligands rarely bind in their lowest calculated energy conformation was confirmed. Additionally, we found that over 60% of the ligands do not bind in a local minimum conformation. While approximately 60% of the ligands were calculated to bind with strain energies lower than 5 kcal/mol, strain energies over 9 kcal/mol were calculated in at least 10% of the cases regardless of the method used. A clear correlation was found between acceptable strain energy and ligand flexibility, while there was no correlation between strain energy and binding affinity, thus indicating that expensive conformational rearrangements can be tolerated in some cases without overly penalizing the tightness of binding. On the basis of the trends observed, thresholds for the acceptable strain energies of bioactive conformations were defined with consideration of the impact of ligand flexibility. An analysis of the degree of folding of the bound ligands confirmed the general tendency of small molecules to bind in an extended conformation. The results suggest that the unfolding of hydrophobic ligands during binding, which exposes hydrophobic surfaces to contact with protein residues, could be one of the factors accounting for high reorganization energies. Finally, different methods for conformational analysis were evaluated, and guidelines were defined to maximize the prevalence of bioactive conformations in computationally generated ensembles.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2004, 47, 10, 2499–2510","title":"Conformational Analysis of Drug-Like Molecules Bound to Proteins: An Extensive Study of Ligand Reorganization upon Binding","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm1013677","date":[{"label":"February 2011","link":"","value":"201102--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm1013677","new_tab":1,"publish_date":"2011 2","publish_date_raw":"20110210000000","publish_year":"2011","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm1013677","reference_text":"S.L. Swann, S.P. Brown, S.W. Muchmore, H. Patel, P. Merta, J. Locklear and P.J. Hajduk; Published in: J. Med. Chem., 2011, 54 (5), pp 1223-1232; Description: We present a probabilistic framework for interpreting structure-based virtual screening that returns a quantitative likelihood of observing bioactivity and can be quantitatively combined with ligand-based screening methods to yield a cumulative prediction that consistently outperforms any single screening metric. The approach has been developed and validated on more than 30 different protein targets. Transforming structure-based in silico screening results into robust probabilities of activity enables the general fusion of multiple structure- and ligand-based approaches and returns a quantitative expectation of success that can be used to prioritize (or deprioritize) further discovery activities. This unified probabilistic framework offers a paradigm shift in how docking and scoring results are interpreted, which can enhance early lead-finding efforts by maximizing the value of in silico computational tools.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2011, 54, 5, 1223–1232","title":"A Unified, Probabilistic Framework for Structure- and Ligand-Based Virtual Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","date":[{"label":"April 2008","link":"","value":"200804--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","new_tab":1,"publish_date":"2008 4","publish_date_raw":"20080417000000","publish_year":"2008","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci7004498","reference_text":"S.W. Muchmore, D.A. Debe, J.T. Metz, S.P. Brown, Y.C. Martin and P.J. Hajduk; Published in: J. Chem. Inf. Model., 2008, 48 (5), pp 941-948; Description: A wide variety of computational algorithms have been developed that strive to capture the chemical similarity between two compounds for use in virtual screening and lead discovery. One limitation of such approaches is that, while a returned similarity value reflects the perceived degree of relatedness between any two compounds, there is no direct correlation between this value and the expectation or confidence that any two molecules will in fact be equally active. A lack of a common framework for interpretation of similarity measures also confounds the reliable fusion of information from different algorithms. Here, we present a probabilistic framework for interpreting similarity measures that directly correlates the similarity value to a quantitative expectation that two molecules will in fact be equipotent. The approach is based on extensive benchmarking of 10 different similarity methods (MACCS keys, Daylight fingerprints, maximum common subgraphs, rapid overlay of chemical structures (ROCS) shape similarity, and six connectivity-based fingerprints) against a database of more than 150 000 compounds with activity data against 23 protein targets. Given this unified and probabilistic framework for interpreting chemical similarity, principles derived from decision theory can then be applied to combine the evidence from different similarity measures in such a way that both capitalizes on the strengths of the individual approaches and maintains a quantitative estimate of the likelihood that any two molecules will exhibit similar biological activity.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2008, 48, 5, 941–948","title":"Application of Belief Theory to Similarity Data Fusion for Use in Analog Searching and Lead Hopping","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","date":[{"label":"June 2007","link":"","value":"200706--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","new_tab":1,"publish_date":"2007 6","publish_date_raw":"20070626000000","publish_year":"2007","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci700052x","reference_text":"G.B. McGaughey, R.P. Sheridan, C.I. Bayly, J.C. Culberson, C. Kreatsolas, S. Lindsley, V. Maiorov, J.-F. Truchon and W.D. Cornell; Published in: J. Chem. Inf. Model., 2007, 47 (4), pp 1504-1519; Description: Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. Results for all virtual screening methods are database dependent and can vary greatly for particular targets.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2007, 47, 4, 1504–1519","title":"Comparison of Topological, Shape, and Docking Methods in Virtual Screening","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm0603365","date":[{"label":"December 2006","link":"","value":"200612--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm0603365","new_tab":1,"publish_date":"2006 12","publish_date_raw":"20061213000000","publish_year":"2006","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm0603365","reference_text":"P.C.D. Hawkins, A.G. Skillman and A. Nicholls; Published in: J. Med. Chem., 2007, 50 (1), pp 74-82; Description: Ligand docking is a widely used approach in virtual screening. In recent years a large number of publications have appeared in which docking tools are compared and evaluated for their effectiveness in virtual screening against a wide variety of protein targets. These studies have shown that the effectiveness of docking in virtual screening is highly variable due to a large number of possible confounding factors. Another class of method that has shown promise in virtual screening is the shape-based, ligand-centric approach. Several direct comparisons of docking with the shape-based tool ROCS have been conducted using data sets from some of these recent docking publications. The results show that a shape-based, ligand-centric approach is more consistent than, and often superior to, the protein-centric approach taken by docking.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2007, 50, 1, 74–82","title":"Comparison of Shape-Matching and Docking as Virtual Screening Tools","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/21661059/","date":[{"label":"May 2011","link":"","value":"201105--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/21661059/","new_tab":1,"publish_date":"2011 5","publish_date_raw":"20110510000000","publish_year":"2011","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/21661059/","reference_text":"J.M. Word and A. Nicholls; Published in: Proteins: Structure, Function and Bioinformatics, 2011; Description: The results of two rounds of blind pKa predictions for ionizable residues in staphylococcal nuclease using OpenEye's legacy protein pKa prediction program based on the Zap Poisson–Boltzmann solver were submitted to the 2009 prediction challenge organized by the Protein pKa Cooperative and first round predictions were discussed at the corresponding June 2009 Telluride conference. To better understand these results, 21 additional sets of predictions were performed with the same program, varying the internal dielectric, reference pKa, partial charge set, and dielectric boundary. The internal dielectric (ϵp) and dielectric boundary were the two most important factors contributing to the quality of the predictions. Although the lowest overall errors were observed with a molecular dielectric boundary at ϵp = 8, predictions using a smooth Gaussian dielectric boundary performed almost as well at lower ϵp values because the Gaussian boundary implicitly accounts for a significant level of solvent penetration. Improved pKa predictions with the Gaussian boundary methodology will require better prediction and modeling of structural changes due to changes in ionization state, perhaps without resorting to the more exhaustive sampling of conformational states used by other recent continuum methods. Proteins 2011; © 2011 Wiley-Liss, Inc.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>Proteins. 2011 Dec;79(12):3400-9.</span>","title":"Application of the Gaussian dielectric boundary in Zap to the prediction of protein pKa values","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/jm070549%2B","date":[{"label":"January 2008","link":"","value":"200801--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/jm070549%2B","new_tab":1,"publish_date":"2008 1","publish_date_raw":"20080124000000","publish_year":"2008","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/jm070549%2B","reference_text":"A. Nicholls, D.L. Mobley, J.P. Guthrie, J.D. Chodera, C.I. Bayly, M.D. Cooper and V.S. Pande; Published in: J. Med. Chem., 2008, 51 (4), pp 769-779; Description: Experimental data on the transfer of small molecules between vacuum and water are relatively sparse. This makes it difficult to assess whether computational methods are truly predictive of this important quantity or merely good at explaining what has been seen. To explore this, a prospective test was performed of two different methods for estimating solvation free energies: an implicit solvent approach based on the Poisson–Boltzmann equation and an explicit solvent approach using alchemical free energy calculations. For a set of 17 small molecules, root mean square errors from experiment were between 1.3 and 2.6 kcal/mol, with the explicit solvent free energy approach yielding somewhat greater accuracy but at greater computational expense. Insights from outliers and suggestions for future prospective challenges of this kind are presented.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Med. Chem. 2008, 51, 4, 769–779","title":"Predicting Small-Molecule Solvation Free Energies: An Informal Blind Test for Computational Chemistry","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://pubs.acs.org/doi/abs/10.1021/ci050488t","date":[{"label":"February 2006","link":"","value":"200602--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://pubs.acs.org/doi/abs/10.1021/ci050488t","new_tab":1,"publish_date":"2006 2","publish_date_raw":"20060202000000","publish_year":"2006","reference_label":null,"reference_link":"http://pubs.acs.org/doi/abs/10.1021/ci050488t","reference_text":"S.P. Brown and S.W. Muchmore; Published in: J. Chem. Inf. Model., 2006, 46 (3), pp 999-1005; Description: We have developed a system for performing computations on an enterprise grid using a freely available package for grid computing that allows us to harvest unused CPU cycles off of employee desktop computers. By modifying the traditional formulation of Molecular Mechanics with Poisson−Boltzmann Surface Area (MM-PBSA) methodology, in combination with a coarse-grain parallelized implementation suitable for deployment onto our enterprise grid, we show that it is possible to produce rapid physics-based estimates of protein−ligand binding affinities that have good correlation to experimental data. This is demonstrated by examining the correlation of our calculated binding affinities to experimental data and also by comparison to the correlation obtained from the binding-affinity calculations using traditional MM-PBSA that are reported in the literature.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"J. Chem. Inf. Model. 2006, 46, 3, 999–1005","title":"High-Throughput Calculation of Protein-Ligand Binding Affinities: Modification and Adaptation of the MM-PBSA Protocol to Enterprise Grid Computing","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","date":[{"label":"October 2004","link":"","value":"200410--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","new_tab":1,"publish_date":"2004 10","publish_date_raw":"20041012000000","publish_year":"2004","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/15481091/","reference_text":"N.V. Prabhu, P. Zhu and K.A. Sharp; Published in: J. Comp. Chem., 2004, 25 (16), pp 2049-2064; Description: A fast stable finite difference Poisson–Boltzmann (FDPB) model for implicit solvation in molecular dynamics simulations was developed using the smooth permittivity FDPB method implemented in the OpenEye ZAP libraries. This was interfaced with two widely used molecular dynamics packages, AMBER and CHARMM. Using the CHARMM-ZAP software combination, the implicit solvent model was tested on eight proteins differing in size, structure, and cofactors: calmodulin, horseradish peroxidase (with and without substrate analogue bound), lipid carrier protein, flavodoxin, ubiquitin, cytochrome c, and a de novo designed 3-helix bundle. The stability and accuracy of the implicit solvent simulations was assessed by examining root-mean-squared deviations from crystal structure. This measure was compared with that of a standard explicit water solvent model. In addition we compared experimental and calculated NMR order parameters to obtain a residue level assessment of the accuracy of MD-ZAP for simulating dynamic quantities. Overall, the agreement of the implicit solvent model with experiment was as good as that of explicit water simulations. The implicit solvent method was up to eight times faster than the explicit water simulations, and approximately four times slower than a vacuum simulation (i.e., with no solvent treatment).","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Chem. 2004 Dec;25(16):2049-64.</span>","title":"Implementation and testing of stable, fast implicit solvation in molecular dynamics using the smooth-permittivity finite difference Poisson-Boltzmann method","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","date":[{"label":"January 2004","link":"","value":"200401--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","new_tab":1,"publish_date":"2004 1","publish_date_raw":"20040123000000","publish_year":"2004","reference_label":null,"reference_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200330847","reference_text":"G.E. Kellogg, S. Phatak, A. Nicholls and J.A. Grant; Published in: QSAR & Combinatorial Science, 2004, 22 (9-10), pp 959-964; Description: A CoMFA 3D QSAR (Quantitative Structure-Activity Relationships) study was performed on five diverse data sets that have been previously published or are otherwise generally available to assess the value of the ZAP electrostatic potential field (calculated from a solution of the Poisson-Boltzmann Equation) as compared to the Coulombic field as implemented in standard CoMFA. The ZAP field showed an average improvement of 0.114 in q2 (leave-one-out cross-validation) as compared to the Coulombic field, and the steric/ZAP combination field showed an improvement of 0.128 in q2 as compared to the Both (steric and electrostatic) field combination of CoMFA. However, the enhancement is not monolithic – some of the data sets in this study showed a much larger preference for the ZAP field than others. The ZAP field appears to be more physically realistic than the Coulombic field and should be of significant value in QSAR studies of some data sets.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<p>QSAR &amp; Combinatorial Science Volume22,&nbsp;Issue9-10, January 2004.</p>","title":"Validation of Poisson-Boltzmann Electrostatic Potential Fields in 3D QSAR: A CoMFA Study on Multiple Datasets","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","date":[{"label":"March 2001","link":"","value":"200103--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","new_tab":1,"publish_date":"2001 3","publish_date_raw":"20010320000000","publish_year":"2001","reference_label":null,"reference_link":"https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.1032","reference_text":"J.A. Grant, B.T. Pickup and A. Nicholls; Published in: J. Comp. Chem., 2001, 22 (6), pp 608-640; Description: This work introduces a continuous smooth permittivity function into Poisson–Boltzmann techniques for continuum approaches to modeling the solvation of small molecules and proteins. The permittivity function is derived using a Gaussian method to describe volume exclusion. The new method allows a rigorous determination of solvent forces within a grid-based technology. The generality of approach is demonstrated by considering a range of applications for small molecules and macromolecules. We also present a very complete statistical analysis of grid errors, and show that the accuracy of our Gaussian-based method is improved over standard techniques. The method has been implemented in a new code called ZAP, which is freely available to academic institutions.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<p>Journal of Computational Chemistry: Volume 22, Issue 6, Pages: 565-672, 30 April 2001.</p>","title":"A Smooth Permittivity Function for Poisson-Boltzmann Solvation Methods","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/20455007/","date":[{"label":"May 2010","link":"","value":"201005--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/20455007/","new_tab":1,"publish_date":"2010 5","publish_date_raw":"20100509000000","publish_year":"2010","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/20455007/","reference_text":"M.T. Geballe, A.G Skillman, A. Nicholls and J.P. Guthrie; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4), pp 259-279; Description: The interactions between a molecule and the aqueous environment underpin any process that occurs in solution, from simple chemical reactions to protein–ligand binding to protein aggregation. Fundamental measures of the interaction between molecule and aqueous phase, such as the transfer energy between gas phase and water or the energetic difference between two tautomers of a molecule in solution, remain nontrivial to predict accurately using current computational methods. SAMPL2 represents the third annual blind prediction of transfer energies, and the first time tautomer ratios were included in the challenge. Over 60 sets of predictions were submitted, and each participant also attempted to estimate the error in their predictions, a task that proved difficult for most. The results of this blind assessment of the state of the field for transfer energy and tautomer ratio prediction both indicate where the field is performing well and point out flaws in current methods.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):259-79.</span>","title":"The SAMPL2 blind prediction challenge: introduction and overview","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100430000000","publish_year":"2010","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/20432055/","reference_text":"B.A. Ellingson, A.G. Skillman and A. Nicholls; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4), pp 335-342; Description: A prospective study of aqueous solvation energies was done using the SM8 and Zap TK models for a variety of geometries. CM4M charges calculated with M06 and M06-2X were found to yield similar results for the SM8 model. Zap TK calculations were primarily done with AM1BCC charges but limited attempts to use charges derived from DFT showed promise. The OMEGA application quickly generated conformations that performed well with both solvation models, while the use of computationally expensive DFT optimized geometries yielded increased RMSE and MSE. It is shown that increasing levels of gas phase geometry optimization yield increasingly unfavorable solvation energy for single conformer models.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):335-42.</span>","title":"Analysis of SM8 and Zap TK calculations and their geometric sensitivity","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100428000000","publish_year":"2010","reference_label":null,"reference_link":"https://link.springer.com/article/10.1007/s10822-010-9358-0","reference_text":"A.G. Skillman, M.T. Geballe and A. Nicholls; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4) pp 259-279; Description: This special issue reports on the third annual Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge and workshop. The SAMPL2 challenge was open to all and allowed participants to make blind predictions of tautomer ratios and small-molecule hydration energies. Participants were asked to make specific predictions of experimental values that were not readily available. In order to maximize participation in SAMPL2, the challenge was announced at several conferences and on CCL (ccl.net, the computational chemistry list), and practitioners who had published articles about tautomer prediction or transfer energies within the last few years were invited directly. Prior SAMPL challenges covered transfer energies, affinity predictions, virtual screening and protein-ligand co-crystal pose prediction and have been discussed elsewhere [JMC 2008, 51(4):769–779; JPC B 2009, 113(14):4501–4537]. This introduction will comment briefly on the results from SAMPL2, discuss the importance and design of prospective predictions, and introduce the next challenge, SAMPL3.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):257-8.&nbsp;</span>","title":"SAMPL2 challenge: prediction of solvation energies and tautomer ratios","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","date":[{"label":"April 2010","link":"","value":"201004--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","new_tab":1,"publish_date":"2010 4","publish_date_raw":"20100406000000","publish_year":"2010","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/20372975/","reference_text":"A. Nicholls, S. Wlodek and J.A. Grant; Published in: J. Comput. Aided Mol. Des., 2010, 24 (4), pp 293-306; Description: An account is given of our contributions to the SAMPL2 challenge for vacuum-water transfer energies. These contributions include different charge sets and radii used with Poisson–Boltzmann continuum theory applied to a single low-energy conformation. A rationale for this approach is given, including a summary of what we have learnt over previous SAMPL events. The results strongly suggest the need for new and repeated experimental measurements, both to clarify what appears to be experimental discrepancies in older measurements and to advance the field in a statistically sound manner.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2010 Apr;24(4):293-306.&nbsp;</span>","title":"SAMPL2 and continuum modeling","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://pubmed.ncbi.nlm.nih.gov/18217218/","date":[{"label":"January 2008","link":"","value":"200801--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://pubmed.ncbi.nlm.nih.gov/18217218/","new_tab":1,"publish_date":"2008 1","publish_date_raw":"20080123000000","publish_year":"2008","reference_label":null,"reference_link":"https://pubmed.ncbi.nlm.nih.gov/18217218/","reference_text":"P.C.D. Hawkins, G.L. Warren, A.G. Skillman and A. Nicholls; Published in: J. Comp. Aided Mol. Design, 2008, pp 179-190; Description: The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<span>J Comput Aided Mol Des. 2008 Mar-Apr;22(3-4):191-2.&nbsp;</span>","title":"How to do an evaluation: pitfalls and traps","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"http://www.sciencedirect.com/science/article/pii/S0009261407005817","date":[{"label":"June 2007","link":"","value":"200706--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"http://www.sciencedirect.com/science/article/pii/S0009261407005817","new_tab":1,"publish_date":"2007 6","publish_date_raw":"20070613000000","publish_year":"2007","reference_label":null,"reference_link":"http://www.sciencedirect.com/science/article/pii/S0009261407005817","reference_text":"J.A. Grant, B.T. Pickup, M.J. Sykes, C.A. Kitchen and A. Nicholls; Published in: Chemical Physics Letters, 2007, 441 (1-3), pp 163-166; Description: This work introduces the ‘Sheffield Solvation’ model for calculating the electrostatic component of molecular solvation energy. The resulting formula can be included in standard modelling technology with very low computational cost. The model replaces detailed information about local atomic environments (such as found in Generalised Born approaches), by using two global parameters. The methodology is validated against accurate Poisson–Boltzmann calculations, and compared to Generalised Born results.","resource_type":{"createdAt":1711022321119,"createdByUserId":0,"id":4,"isHubspotDefined":false,"label":"Publications","labelTranslations":{},"name":"Publications","order":0,"type":"option","updatedAt":1711022321119,"updatedByUserId":0},"table_id":5340264,"tagLabel":"Publications","tags":null,"text_snippet":"<p>Chemical Physics Letters, Volume 441, Issues 1–3, 13 June 2007, Pages 163-166.</p>","title":"A simple formula for dielectric polarisation energies: The Sheffield Solvation Model","topics":[],"types":[{"label":"Publications","link":"","value":"Publications"}],"years_within":[]},{"bottom_link":"https://cdn2.hubspot.net/hubfs/73182/ligand-based-design-workflow.pdf","date":[{"label":"March 2007","link":"","value":"200703--"}],"featured":0,"has_bottom_link":true,"has_reference":true,"industries":[],"interests":[],"link":"https://cdn2.hubspot.net/hubfs/73182/ligand-based-design-workflow.pdf","new_tab":1,"publish_date":"2007 3","publish_date_raw":"20070304000000","publish_year":"2007","reference_label":null,"reference_link":"https://cdn2.hubspot.net/hubfs/73182/ligand-based-design-workflow.pdf","reference_text":"Paul Hawkins and Geoff Skillman; Published in: OpenEye Scientific Software; Abstract: This paper introduces a ligand-based approach to virtual screening based on a new method of describing molecular shape and chemistry as embodied in the application ROCS (Rapid Overlay of Chemical Structures). 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